{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib——简单图\n",
    "### CopyRight by heibanke"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 画图——基础\n",
    "\n",
    "了解图的基本组成部分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAEDCAYAAAAhsS8XAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114108190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "x = [1,2,3,1]\n",
    "y = [1,3,0,1]\n",
    "\n",
    "plt.plot(x,y)\n",
    "\n",
    "#plt.title('Triangle')\n",
    "#plt.ylabel('Y axis')\n",
    "#plt.xlabel('X axis')\n",
    "\n",
    "#plt.xticks([1,6])\n",
    "#plt.yticks([1,6])\n",
    "#plt.xticks([1,6],['a','b'])\n",
    "\n",
    "#plt.ylim([-1,4])\n",
    "#plt.xlim([-1,4])\n",
    "\n",
    "plt.grid(True,color='r')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 画图——样式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据线的样式设置\n",
    "\n",
    "    颜色缩写    全称\n",
    "    b          blue\n",
    "    c          cyan\n",
    "    g          gree\n",
    "    k          black\n",
    "    m          magenta\n",
    "    r          red\n",
    "    w          white\n",
    "    y          yellow\n",
    "   \n",
    "   \n",
    "    线型缩写    含义\n",
    "    --         --虚线\n",
    "    -.         -.虚线\n",
    "    :          .虚线\n",
    "    -          实线\n",
    "    \n",
    "    marker类型参考 \n",
    "    http://www.labri.fr/perso/nrougier/teaching/matplotlib/#line-properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAEDCAYAAAAVyO4LAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKCyGctwKhUJhMf4faICnQvt85LYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1137e43d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = [1,2,3,1]\n",
    "y = [1,3,0,1]\n",
    "\n",
    "# np.array将列表转换成numpy的数组后可以支持广播broadcast运算\n",
    "plt.plot(x,y,color='r',linewidth='2',linestyle='--',marker='D', label='one')\n",
    "plt.plot(np.array(x)+1,np.array(y)+1,color='g',linewidth='3',linestyle=':',marker='o', label='two')\n",
    "plt.plot(np.array(x)+2,np.array(y)+3,color='k',linewidth='1',linestyle='-.',marker='>', label='three')\n",
    "\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "#plt.legend(loc='upper left')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 画图——中文"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 下载参考资料里的微软雅黑字体msyh.ttf\n",
    "2. 将字体拷贝到matplotlib安装位置 /matplotlib/mpl-data/fonts/\n",
    "3. 修改配置文件 /matplotlib/mpl-data/matplotlibrc\n",
    "\n",
    "    1) backend      : TkAgg  #mac需要修改，windows默认就是TkAgg\n",
    "    \n",
    "    2) font.family         : Microsoft YaHei\n",
    "    \n",
    "    3) font.serif          : Microsoft YaHei, ......#(后面的不变，只在前面加雅黑字体)\n",
    "    \n",
    "    OK, 大功告成，试试效果吧"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEdCAYAAADn46tbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112d73850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = [1,2,3,1]\n",
    "y = [1,3,0,1]\n",
    "\n",
    "x2 = np.array(x)+1\n",
    "y2 = np.array(y)+1\n",
    "\n",
    "plt.plot(x,y,'g',label=u'第一个', linewidth=5)\n",
    "plt.plot(x2,y2,'c',label=u'第二个',linewidth=5)\n",
    "\n",
    "plt.title(u'两个三角形')\n",
    "plt.ylabel(u'Y轴')\n",
    "plt.xlabel(u'X轴')\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 画图——公式TeX, 文本和标注支持"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWoAAAEDCAYAAAAcI05xAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ee0f690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure() #figsize=(10,6)\n",
    "ax= fig.add_subplot(111)\n",
    "ax.set_xlim([1, 6]);\n",
    "ax.set_ylim([1, 9]);\n",
    "ax.text(2, 8,  r\"$ \\mu \\alpha \\tau \\pi \\lambda \\omega \\tau \\\n",
    "    lambda \\iota \\beta $\",color='r',fontsize=20);\n",
    "ax.text(2, 6, r\"$ \\lim_{x \\rightarrow 0} \\frac{1}{x} $\",fontsize=20);\n",
    "ax.text(2, 4, r\"$ a \\ \\leq \\ b \\ \\leq \\ c \\ \\Rightarrow \\ a \\\n",
    "    \\leq \\ c$\",fontsize=20);\n",
    "ax.text(2, 2, r\"$ \\sum_{i=1}^{\\infty}\\ x_i^2$\",fontsize=20);\n",
    "ax.text(4, 8, r\"$ \\sin(0) = \\cos(\\frac{\\pi}{2})$\",fontsize=20);\n",
    "ax.text(4, 6, r\"$ \\sqrt[3]{x} = \\sqrt{y}$\",fontsize=20);\n",
    "ax.text(4, 4, r\"$ \\neg (a \\wedge b) \\Leftrightarrow \\neg a \\\n",
    "    \\vee \\neg b$\");\n",
    "ax.text(4, 2, r\"$ \\int_a^b f(x)dx$\",fontsize=20);\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Annotate各种格式可参考文档\n",
    "\n",
    "http://matplotlib.org/users/annotations_guide.html#annotating-with-arrow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAM4AAADLCAYAAAAm0qx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLJYQsIFjsYSADRyLJQT+P2Z3TyI/UeRAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11531a3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(1, figsize=(3,3))\n",
    "ax = plt.subplot(111)\n",
    "\n",
    "ann = ax.annotate(\"Test\",\n",
    "                  xy=(0.2, 0.2), \n",
    "                  xytext=(0.8, 0.8), \n",
    "                  size=20, va=\"center\", ha=\"center\",\n",
    "                  bbox=dict(boxstyle=\"round4\", fc=\"w\"),\n",
    "                  arrowprops=dict(arrowstyle=\"-|>\",\n",
    "                                  connectionstyle=\"arc3,rad=0.2\",\n",
    "                                  fc=\"r\"), \n",
    "                  )\n",
    "ax.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. 画图——多子图结构"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table class=\"table table-bordered\">\n",
    "<tr><td>1</td><td>2</td></tr>\n",
    "\n",
    "<tr><td>3</td><td>4</td></tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEVCAYAAADn6Y5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXmYlNWVuN/DInRDAwoIGBRQaEBcAFFcRrvVaJy4ZASX\nSTSCGsnkl0lQ45ZFuyFRnIDRaKIjGUfFxIyyKRrHmEkoFDTGBFFcABdaIosBZWnoRpY+vz/uV9W1\ndtdeX1Wd93m+p+vb7r1f1a3Tp849i6gqhmEYRvnQodADMAzDMPKLCX7DMIwywwS/YRhGmWGC3zAM\no8wwwW8YhlFmmOA3DMMoM0zwG75FRB4Wka/lsP21InJIrtpvp+86EflBBvcXbOxG8WOC3yhnijmI\npZjHbhQYE/xGOSOFHkAGFPPYjQJjgt9IiIgMEpH3RORnIvKRiLwgIl28c8eIyFLv/FIRGe4drxOR\nR0TkTRH5pmeuuVdE/uaZJ84Qkf8VkfUi8mPvnkoRec5r600RGdXGmH4iItPD9p8VkS+KyNUi8oGI\nNIjI2VH3vCQiXwzbXysifaOuuVhE3hKR90XkcRHp7h0fJiIvi8i7InKHiOyNM6Z1IjLEe32wN4au\nIvKk97693c77fJj3nrwnIstF5GTveEcR+aX3XH/w3qMY01cmYzfKExP8RnsMAeap6iDgAOBCEekI\nzAVuUdVhwE+BX4fdMxo4TlUf9PYPUdXjgF8CTwP/DowBrhWRbjjt9QdeWw8C32tjPE8AXwEQkZ7A\nkcAfgbuAk1R1MPDnqHseD7vneGCVqm4OnhSRYcCdwJmqOhTYBNzmnX4EuFdVRwJriG9ieTLYPnAh\n8D/AOUA37307pY3nAZgDPOY9/zXA4yLSGbgaGAQMBa7Ava8RZGHsRhligt9oj/Wq+rL3eilOEA0H\nGlV1KYCqLgIOCWqawHOqGq5dPuv9fRl4U1U/UNV/AH8H+qvqLmCwiNwHfB34QqLBqOpKoJOIDALO\nBRaqSzj1IvALETlSVXdE3TYPJ4jBCebfRp0/y2vnE2//P4EzRKQSGKGq/+Md/zXxCRf8E4HfACuB\no0XkBmBfoufx+hilqo97z/c3YD0wAjgTeFAdG4E/xWki07EbZYgJfqM9Pg97vRfoCHQiVntUoMV7\nvTPq3B7v7/6o9vYDHUXkm8AUYDZwO+3br58E/gWYgBOyqOoFwEJgkYhMjBiY0+7fF5FjgS971wXH\njPc8LUSyH6jAPXOQA+INRlX/AnxBRIYCvVV1pap+AIwF+gJviEiPBM8S770U3D+LSlrfO4DOCe5P\ne+xGeWKC32iPeEL4XaC3iJwCICLnAx+oalOafRwFLPa0+S8lcf2TwPnAYaq63BvDMFX9LfBz4ptW\nfgvcBLyvqo3eseCz/RGYKCIHe/tTgP9V1U+BRhE51zv+zTbGtBBnbnrCG89AYKeq3gx8BgyOd5P3\n6+RDEfmqd99Y4ECcaeYvwFXiOByn3UeTjbEbZYYJ/iJARCaJyGsF6j7GLuyZcS4F7hGR1Tib/RXJ\n3h/n3MPAN0VkJbC7vXtV9V2gN/BU2OG5IrIGuBi4N85tT+HMPI9Ht6+qbwPTgJe85+mBs5sDTAZ+\nJiKrcN+X/Qme5Qngn8PaHw6s9u5bpqpvJrgP4HLc878H3Af8q6ruB+4BugAN3uslYf1nc+x5w1vs\n/2mhx1HuiOXj9z8iMgn4tqqekMS1A3Ha87Dcj6x4EJEDcFr0cFX9vL3rE7QxEAh4i6h5R0T+D6gP\nrq2keG9Bxx42joeBzap6UyHHUe6Yxl969AIOL/QgfMg3cIvOKQl9Efknz62yA/BD4LmcjC5+39Ui\nMsB7fRruV8TfUri/YGM3/I0Jfp8gIi0i8lXPj3uHiDwtIr0TXDvU8+neKiIfisiPPDtwDfCmd81+\nEfnvvD6ETxGRJ4FJwI/SuP08nPfRB7jF1nTaSJe+wFIRaQBmAReranMK9xds7CLymohcG7Y/UESa\ncOsX4dedIyJ/FZFGEXlDRP4l7FyFiDwkIlu8WIZpIrIZI2PM1OMTRKQFWIazyzbifME/VtUrwk09\nIlIBrAJ+hbNlDwEWALNU9QFxwU9vqmrHQjyHYQCIyLeBy1Q1GIx2A3A8sAvYoqo3eV5WLwGX4Rap\nz8Itwp+gqm+JyC+Bo4Gv4rzJ5gODVPXgmA6NlDCN31/cEebjXo/T2KI5H9ilqj9R1R2q+gYugOrr\n3nkL5Tf8wOPAaG9tAeBfcQFl4fNzCvAbVX1GVZtU9WlcgF8wOnkScKOqrlfVdcAd+Rl66WOC3198\nFPb6E6DKs8+GMwh4P+pYAzDAe20/4YyCo6pbcYF7F3vRxf2B56MuGwy8F3WsARggLqVGJW5BPshn\nORlsGdKp0AMwIgi36R+JM/W0iEQo8euBI6LuG0LrPw0T/IZfeBS3rtAdp9lrEnN5MLAa2I4LTDsU\n2OqdM6eFLGEav7+4TUQGiMgROFNPvMXZZ4GDROSHIlLl2UlvwOXBAe9LIiKjEy0OG0aeeB73C3Uy\nzswTzcPAFSJynrhEfRfgAvj+W1X3AL8Hfiou8d0o4Lr8DLv0SUvwi8s8aH7i2ec5XIKxZbi8LDOi\nL/AiPc8Gvgh8jAsc+g9Vneud34hb+F0GfD8/wzaMWLwgtCdwi7nvxjn/Cs6OPwOXXO4HwHmePR+c\nC67ivJIexqX02JWHoZc8KXn1iEgVLpPgGcATqjpFRA4C7sflJRHgR6oaDFu/E7di/xkwWVVfz/L4\nSwbPq+coVX2n0GMpZ0SkK3Coqkbbno00EJEXgAWq+p9ZaGsqcIGqnpn5yMqbVDX+FpwLYfhPrr7A\n/apajcuA+J9e0MgZwMnAYbg0u+ZTbvgWz2y2ELeofmPY8Uu8WIk1InJl2PHh4uoMPCciIwoxZj8j\nIgeKyKXAsThlMZ02viIiIzx//lpcrqVfZXGYZUtKi7te+tzFInJY2LHVuMUYVPUDEdmDywx4IfCI\nlzL3/0Skj4gc7LkqGrHYomxhCSo1zwAnAohLMz0LOAH3+awQkUWq+qk377/rCbcxuNgKo5XfACNx\nQWfpJu87FPgFcBCwFpgelmbayICsevWIyJeBv6rqThE5lMgkWhtwLocm+ONgAVeFJZ5Sg1toDKjq\nJgAR+SMuR/6T3v4sYBxwSZ6H63tU9ctZaOMXOMFvZJmsefWISDVukSaY/vUAIvOEt+CD7ICGkQKH\nEhlbsZ7WeAlU9QZcENIteR6XYWREVjR+cfVGnwAuV9WPvcMbiaykdAjOCyX6XjNxGDlFVdONZk6o\nvIjLc38uLvbirng329w2ck26czsTjV8APJPOPOAqr5BGkN8Bk0Skg4icBaxW1W3xGlLVvG+TJk0q\nSL+F7LscnzlDNgIDw/YH4pKeoaq/U9X/p6qXqqvAFZe6ujoWL15cFu91Ifsup34XL15MXV1dRhM7\nJY3fW+x6HReJ19XLBik4recJcWF5ios6XQjUAB8CW2jNv+ELBg8eXHZ9l+Mzp0lQi3oBuENE+uC+\nKyfhTDu+phw/53LrN1NS9erZCaQSuDXV2wzD1yRQaq7B5bH/M06huV5TS4tsGL6kbHP19OrVq+z6\nLsdnTpZ2lJq0/NAB6uvr0701bcrxcy6nfmtra6mtrWXatGlpt1G2uXpGjx5ddn2X6jOrKrdMuwVV\n/62l1tfXEwgE8tpnqX7O1q8jEAhkrFCUreCvra0tu75L9ZnnPzOf+/90PwueXZCzPoqJUv2crd/s\nUfAKXCKihR6DUbyoKiddchKvjnqV8W+P55UnXyE89a+IoOm7c2aEzW0jl2Qyt8tW48/3z28/9F2K\nzzz/mfmsrFoJAiu7r/Sd1l8IU08pfs7Wb2SfZuoxyhZVZdZjs2g6zKWCaRrUxMw5M31l66+vry9a\nc4DhT2prazMW/GbqMYqWeYvmMempSTQNas0BVtlQyZwJc5h4/kTATD1G6ZLJ3E7LndNylht+YNlf\nlzFu/zhkbevcV1WWvrY0JPgLTVDjN63fyBaBQCBzE1MqocJAFS4idzswO+z4VFwyq3eBc8KO34kL\ncX8DGJOgTS0EixcvLki/hey7HJ/Zm1+pzPGuwLBU7mmjrbw8YzTl+DmXW7+qqc/t8C3jQixefdhv\n4XJvTwAeskIsRrGRRiGW47xCLPNFxB8/L4ySQ3MVo5LOfwtcnczZ3uvv4QokBM8txRWuuA+XuC14\n/O/AwXHayuH/RKPcIUmtCOgGnA5cFTa3uwPrgP5AP1zStt7eueD62IHAwwnazPPTGsVKS0uL3lx/\ns7a0tEQcn/v0XK06rUrnLZoXc0+yczvelg2vnng5yw+JczxYiMUwfIeq7lLVxUTWjAgVYlHVT4Bg\nIRa8Lx7ADcDP8zpYo2jRBBp8vCBEVee11nh6Y9a91bIh+OPlLN+X4LhvCrGYr3Px9Z3oS5NDEhZi\n8dKNzwCeUdUV+RpQMhT751zs/bY1T1MR8LmMUclGkrbogivBnOVJFWIBmDx5cii9aa9evRg9enTI\nCyL4xmZ7P0iu2m9rf8WKFXntzw/7QTJpb/4z87l3wb1UdK6g7gd1ca+/5557WLFiRbbS5balvNyO\nq83bW0RGqurD8RoYPXo0o0ePZvDgwTa3S2x/8eLF/OQ/fkJNTQ0iEjq/ZccW7v/T/VR0rqDm5JqI\n62+767aQgD+o+0GICFt2bHECvgFWNK5gwbMLmHDeBG676zaahrTGqFz/o+tZNG8RIkJDQwMZkY59\nCGfj/5X3eizwFq7A+pHAW97xCcAfcL8qzgJeSNBWGhYxo9xoaWnR8ReNV+rQ8ReNj7GFJoLUvXrC\n16++DjwUdu4x4CsptKV1dXUF9fwwMicV+3tb83Tu03O18spKpR6tnFyp8xbNi7ieekL3PfnUk6Fr\ng1vwnsWLF2tdXV3+bPwi0l1E3sO5aV4kImtwLp6/Bt4G5gLf8C5fCLyDK8QyA/j3VPoyjHDynJoh\nvBDL2SLSR0T64wqxvJDLjo3CoVmwvyeap8Hro6PM5y2aF7oeCN336NxHGbd/HDVra0LbuJZxLH1t\naVaeNSXBr6o7VXWYqg5Q1QNVtVpVl6jqnap6uKqOUtU/e9eqqk5V1cGqOk5V12RlxFkinm2u1Psu\n1mdO9KWJ/oJmQgKlZgSthVheokgKsRTr55yvfrMq4BtaBXxb8zT8HwLQroAfdvgwljy6hMAjgdC2\n5NEl3D397kzephBlW4jFKB4SfWkWPLsgaxG6WkKFWIy2CQr448ceH5o/0QJ+wnkTEJG4GvyE8yY4\nAT+qCRpaBXxLS0vCeZooynzY4cNSFubBSPBMCrFYrh7D91x323Us/2h5RLplVWXsoLHtfmkKnaun\nrq4u9EU18ouq8v3p32fGbTNCc0c1fhrv8LxPwXxPE86bELoWr5r4+LfH873Lv8fkpyfH5Ig6fe/p\nNHZsTGuepkLAS9kwbdq0tOe2afyG78nml8YoPeIJeIiv2berwdO+Bv/o3EcZ1zE72nuhKFuNPxAI\nFEwLK1Tf5fjMhdb4bW7nnnmL5nHFrVfw2E8eizDdRGv2QNY1+Fw975Qpd7Jmze6Y49XVXZk9+xag\nANk5DcNIDsvOmT0SmW5mPTaL5jHN7drmVdV3GnwiAb969To2bYqX3qw+ZOrJhLLV+A3/kuinezqU\no8Zf7CT6/OctmsdVd13Fwzc8HNLsU7HNnzjiRF5f93rObPBtaelASgK+Z8/JbN/+SMzxmpp6AoF6\nwDR+o8SIZ5s1yodkvW6AlGzzN55wI/f8+J6Mx5eOlg6wZEl9zJmePSdnPJ50KFvBX2520EL2m0rf\nidzqipVCmHqK4XOGtk03ybhVRphu1gJD2jbdpFqgJzkBHwDc8+ZLiGfD1JM1wS8i1wP/BnQEZqnq\nAyIyFbgeaAKuU9Xns9WfUZrE+4LnU+tPtrqciHQCTgM6qWrCaF7z409Mpl43J444MeQbv23TNnrR\nq03b/JQpd1JbWx9zfNOmVfTvPyLmeFtmmELiGz9+ERmE+9c3EqjEpWk4GZe2YQwwCPg/4DBV3R91\nr9lBDSDSEyPcNhv0tU6HZO2gIlKFC9Q6A3hCVad4xy/BRfPuA2aol4xNRMYAXwQGqOr1Cdq0uU3y\n/vSQmtdNeG3lcFI1xSSyp2freE1NPZDY1BPvnv79L2b48FExx/3m1bMXUG/rDOwA/hn3BWoC3hWR\ntcBxwF+y1KdRYuQjQrcNgtXlnsFl3UREugOzcIWFFFghIotU9VNVfV1EPsOVHTXaIFnNPlWvm/oZ\nd3PfXStj+vOrph6PiopdjB5dH3O8uvq4kIDPBVkR/Kq6QUTqgFdx+X++BlwEhH8qoVzmfqBY7KCl\n0G+yfReyeLqq7gIWi8hhYYdDhVgARCRYiOXJnA4mQwr1Oasql115Gb95+Ddt2uwh/qJsuOkmvM2P\nPtxG7wO+GNGXAFvWruOtTfXekQD5trVH95tYiHf1XsU7l1sBn4isCH7vZ/I3gd/gzDo/wC23JFWI\nxfLx+yfHeCHf77un353x55XlfPwJC7GE0eZP7XKa29PvmM78l+Yz8dmJTDx/IoFAgCXLloS0+BWN\nK5g+YzqjjhoVSnAGhBZl977Qnf2fD6FXL/d+bdvmLtjySQdPwAefz/XXrds5hAve1vNE7bvz+/Zt\nysr1QQG/bVsDO3duYuBAd7x79wO54YbanH1e2Zzb2bLxfws4UlW/4+3/AXgRQFV/7B17Cfh3VX0j\n6l6zgxo5I1U7qIhMAk5R1SkichPQTVXrvHMzgPWq+gsROQa4CTgKeERVY/wESzFXTyIf+1Rs9js/\n7sjHzetj2t67qRtNn7wdczzXNvhM7OyFIOjV44dcPbuBISLSEegKHIxbzP2ViMwChgAHRgt9o7zJ\nZqBWjthIq7oHrrpcMO34m8DlBRhTQUkUY5GKzX7w7nPZ/saymLZzbaJJZIrZtGl3QezshSRbgv/X\nOG+ID3Gum/+tqq+IyG9wBVqagauz1FdW8Lu9u5T6TdS3jwO1wgux3CEifXDflZOAKQUbVZLk6nNO\n5GMfykM/qgnWQtNgZ7Pf+XFHOjf3pefyyHYaNsVq9ZkToH1be/YFeSG/U5mQrcXdvbgyddHHZ+Cq\nbxlGBH4L1PI8eF4HugNdRaQGuIbWQixKkRRiyQbxfo0lirE469zLea3n8gjN/rVOy6n64BS2b26I\naTtbmn24gN+2rYFevQJAaWvq2cJy9RgFIV6OlVxo/ZarJz2i8+K0FWNx6JEnsb65C5Hr3MoBOzez\n59N3YtouFVt7WrS0wIYN0NgIO3a4rbER9u6FSy9NqSk/+PEbRtJEmAZodecrtNafC4oxO2e8X2OJ\ntPqzzr2cof3OYX2c4KSKnpPZk0K/hfJpTwpViDc3P/8cZs+G7dsjt/37Yd682OsbG2H8eKiqgh49\n3FZVBf36JS34g4u7mVC2gt9v9u5S7je67wIHapU8qXzO0SadKVPuZNlry1k1YnlIuB819lIaNr5N\nS9eT4JVW4deCsqriA4b2C69YGSByPTyWXAj4pJ5ZFXbtgk8/hW3b4NhjY6/Zswcuuwy2bnXbtm3u\n7+efu3uj+33pJWpXrYKePaFPHzjiCPf6wAPjj6FnT1gf69GUb8pW8BuFo5CBWvnG77l6ohfYV69u\n5p0t62D4XgBahu/lnaXr6NE8Dj55NOb+oV46glQYPnwUwdTCGbFrF2ze7LZXX4WamlitvKXFCfgt\nW+Czz6BjR+jd223Ll0OHDpHXd+4MF13kBHdw69XLbfHo1Al++cvMnyUFgr8gC56rJxOK2Q5q+J9C\n2/j96sc/ZcqdrF7dzOubH6LxkvVUPfkFxvS9mjfefZHtp/8FjmzNi8M7lVT+/gSati+OaaetPDQp\n2+ZVnXa9cSNs2uQEeac4uumIEbBunbv+4IOhb1+nbT/9NHTpEnv9ypVOgPfuDRUVid6SoiEbfvwm\n+I2SptCC3y9zO9qkU1tbz5KXj4ILJzkh/04lLJzDAT1uZU/3viS7UFtTU091dde2ywSqOrt3VZXT\nuKM55xx4910n7CsroX9/ty1cGF/TXrcODjoIunWLb3cvEzKa26pa0M0NIf8sXry4IP0Wsu9C9dvS\n0qJfnfRVbWlpyXvf3vwq+7k99+m5WnValc5bNE9VVU877TZl4HilDqUe93fgeO3R4wp1kjpy69lz\nUtzjNTV1sX3ffbfqVVepnnWW6vDhqpWVqlVVqg0N8Qe8fLnqhx+qNjVl9ZnzQSHlSCZz22z8Rs6Z\n/8x8nnr9qaJYvE02H3+yFNqrJ9Kk08iVN0/l3llv8sa7L8LpkQvsnLySfb+Pbwqp6LKD0aOvg+Zm\nt+3eDYMHU10dZxGza1c48US4+GI49FC39eiReJBjxmT8nOVENrx6smbqEZEewIPAqbhI3ZHAt2mn\nEIuffg4b2Ufj5HDJp8tmDvPxDwfqgAOA21X19ThtFnxup2rSqdy9geNHXBbZyJtvUr3zHWaP7gFD\nh7ptyBA4/3xnWzcKgl/8+O8D3lTVr4rIAcBhwLdw/wAGAf8nIjGFWIzSptAVtVIgpXz8wHXAd7zj\ndwFXFmLQQYLFR1SVtZv+yJD+ZyIirFr1EfR7HkZ6i7Ujm+DlmXTdOpY9n/46pp3jw4p5h2huLolF\nUaOVDu1f0j4i0g84SV2KBlR1D3Ah8KSqNqnqu7g0zcdlo79skOlPpWLsO9/9ajBQ6zAvh4sXqFVo\nLTgeqrpLVRcTmTo8lI9fVT8Bgvn4AfqqK8jyGVCV5+HGsGbNbpYsqefFV47m7y3LefGVY1iypJ7G\n3Wvh5FiTjuxdTk3vi6g5bBI1R36bmnE3UnPqbWG548NIQeiXy9wudL+Zki2NfxTQICILcBr+s7hK\nXL4txGLknhII1GorH/8OEQkauDfndVQJUeg3C05pht0z4eMJ7Ov0D3h1HLwaadLpfvjnBN6NE1lq\nlAXZEvwH4wT+CcA2nGbUDwhPw+yrQiyF3g+Sz/5ra2vz2t+yvy5j6PqhyAahV/9esBa2btzKb+f+\nNiT4s91/lguxHEDiYkL3ArNx61k/TtRAXub24YfD2rXQcToMXeGSoJ+8EuZPp/Puw9jzaXBpLeD9\nrWVoTb3N7SJ7Xj8WYjkD+K6q/ou3Pw23GIZaIRajgGRYiOXrQK2qXu2dewyYp6pPJ9lW1gO44hYS\n37WLVW9/yCe918PVrUnUeGg8/fYOZMSIo2LaKcoEZwaQnQCurNj4cWlrjxSR/iLSBfgisBO4VEQq\nRORIfFaIJfq/dTn0net+VZVbpt0S14ZfyPc7DcLz8Z8tIn1EpD8uH/8LBRlRYyMsXMia1c0sWVLP\nkiV1LHl1t/v715k0HvBpqy1/LSFbfu8BHQgE6mO2XAn9Up3bfus3U7KVj79JRL6Dq7p1APCwqt7t\n+UT7shCLkX18XFilXXyZj18VXngBHnoIfv97OPVU2D/anes8H0beD28dD3snQtf19FzdF1bDvp27\n6bTCLdJ2qNyQt+EaRUS6kV/Z2ihQdKORXVpaWnT8RS4SdPxF4wsSpRsPChy5W1dXl1505wsvqI4b\np3rUUaoPPqi6ZYuqukhZaGmNuh04XqElJoLWKF0WL16sdXV1FrlrFJ4i8tcvCqb8x1zWNJ3gAqQe\n3wCP3wfA6tXrnLYfNOucvBIWLijsYI3iI93/GNna8FE+k1LvO1f9hmv7wbwv0Vp/oZ6ZIs3V4zR7\njdl69Lgibo6d0067LXSvze3S71c1s7mdrcVdo4xpy1+/3Kmvr297AbClxcn0JJEua+jwT5GVsDr8\n03I6d3s/o3EaxUMgEMi4zoOlZTYy5rrbrmP5R8sjcvCoKmMHjeXu6XcXcGQ+T8vc1ARXXglnnglT\npkScqq2tj5vj/gsjTuSIE7r48r028otfcvUYZYJqZG53EziJSZidc8MG+MpXYPhwuOKKNlpQ6Pp9\n2D0DEIb2O4fAo/W5G7Dhe4J+/JlQtqYe8+NPn6DbZiqmnGL1d86UoOCP4G9/cwW3L7wQHnvMpTFO\nRNBts3NxvNfFPreLod/a2tqMTT2m8RspoeoSrzWe3sjMOTOZcN6EvKZZLnr+8Af42tfgwQdhwoT4\nkbjApk2rOO20OpdH/4JGqnZPZUzfN6mutiyZRuaYjd9IiXmL5jHpqUk0DWqisqGSORPm+NptMxk7\naDrFV0SkE3Aa0ElV40bzxk3ZsHGj28aOBRLb8mtq6vn3648qqvfayA/ZSNmQzUIsnYEVwDJ1eU6m\n0k4RFu8+E/xFgmprUZVgPphCFFdJhbYEf6rFV6LuHYNLTTJAVa9P0H67czuR4D/ttDo+P/j3RfVe\nG/klk8XdbNr4fwD83RvQ4bQWYZkAPCQicaosFw6zg6ZOJm6bPrXxB4uvXBc8EFZ85WRcNbk7RKR3\n9I3qKm49mauBbdnxblG+18U6t4ut30zJio1fREYC44HHcV+WUBEW4F0RCRZh+Us2+jPyQ7T3zrK/\nLmPc/nHI2khXwqWvLS1KE4Sq7gIWi8hhYYdDxVcARCRYfOVJEakFzgUWq+pzuRzb9t3rSuq9NvxF\nthZ378Vp+Kd4+wOBt8LO+64IS7bS5BZT36n2G510LRO3zUK+3ymSsPiKqgZoTWofJCd2l0zcNm1u\nl36/mZKx4BeRb+E0oPdFJCj42ypgEUM5FmLx+35NTY3z3hnSyK2zbg157/hlfDksVpHU3BWRY4Cb\ngKNE5FpVvSdeY+3N7e7dN1BTUw/Atm0N3nWDqa7uWvD30vb9tZ/VIkPp5noIbsAyXKWt13Ga0mbg\nVuDWsGteAo5NcH+qKSqyguUzaZu5T8/VyisrlXq0cnKlzls0L299ZxOSyGcCTAJme6+/DjwUdu4x\n4CvttZGg3aSzc7a0tOjN9TdnJaupze3S7jcb2TkzXtxV1VNU9VhVHQPcBizE1dz1bREWo21Uw4qk\n4+8i6VmkoMVX0gmKM4x0yUnkrjqPh9/girDMBb6Ri34yIfjzqZz6jtevamzVrFwkXSvk+50IEeku\nIu/hXDcvEpE1wAhai6+8RB6KrwT/0QaD4jL9B2tzu/T7zZSsRu6q6qPAo97rGcCMbLZvZJ94VbNK\nzXsnEaqILqBjAAAgAElEQVS6ExiW4PScbPaVKEK3urorZ5831GoZGHmlbFM2BAKBgv23LlTf0f1G\na5rBBdxcJF0r5PvtB9as2R03UEu1jje3zqJpVKRZLZNUGDa3S7/fTCnbJG1G/KpZRnaJm6QtjEwC\ntYzypDYLSdosV0+ZokWYfiEdCp2PP5irp74+YPn1jawQ8FOunnQxwZ8fNCoKNzzZWpBSTARWaMEf\nnNttJWMLBGKPG0Z7+CVXT1ERDI4ol77nPzOfexfcGzIhBBdwa9bWhLZxLeNY+trSnPRfyPe7kLRb\nejEHlNvcLrd+A1kovVi2i7vlRHARt3lMc2jh0MwI+SH4Ba2u/jNQH3O+urqNIiyGEYdaL833tGnT\n0m7DTD1lQLHl0M8mfjH1GEa2sZq7RohoW34oCjeL7oJ+oS3f+Nmzb0m6nXQKsSRLwpq7hpEmwcXd\njEg310P4BnQBHgRWA2uBqd7xqbj8Pe8C5yS4N+VcFdmgVPOZzH16rladVhXKrROec4dJZC33Tqpk\n8szXXDNDa2rqYrb+/a9U0JitpqYudC9t5DMBqnApRrbj5erxjl8CfAisAa5McO9xuKy084GJCa5J\n+5kzoVTntvUbSVtzu70tWxp/N+B5Vf2mV7TibRF5ndZiLIOA/xORw1Q1YZZOIzM0TkBWeBTutk3b\n6EWvoovCTRT81LPn5EybDhZieQY4ESIKsZwAKLBCRBap6qdR9y5X1b+JyIHAz3D/AAyjKMiK4FfV\nz3CaE6r6qYj8HVeQxbfFWEoxn0m8gCy/LOIm88yJTDerV6/LwYiyVojlBuDnORlgmpTi3LZ+s0vW\nbfwicjTQGeiDz4uxFDNaxLb8tgT8pk3/HXM8C5p9KiRViEVEOgC3A0+r6opkG4/+3AyjEGRV8IvI\nwbgkbZOBKSRZjKUQhViCxwpRXGHFihVce+21GbW3ZccW7v/T/VR0rqDm5Bq27NjitP0G7+GGOK1/\n+ozp1JxcE/Gs+X7e8D4DgQB/+csq3njjEe9o8HytJ+Bb94Pn9+3bRCux5yP372HVqqfIwM052SJC\nt+PMQ71FZKTGKcgOsXN7+67toaR4vatcKV+b25nvF2pu5/N5s1mIJWvunCJyEPAc8ENV/aOI3Ipb\nfPiJd/4l4N81Ki9/oVzeAkWcyErD0i0E0yxcX3c9yz9a3mbof76fOVyz37atgV69BgNta/bbtz+S\n9PH+/S9m+PBRMcfDvXqScXkTkUnAKao6RUS+DtSq6tXeuceAear6dFttJGg3lLKhtrY27ueWC62/\nmOe29Ztcn4EMUzZkq9h6T2ARUKeqf/QO/w6YIyJ3AUPwWTGWQn0xUu07nmkgXVt+rp4516abiopd\njB5dH3O8uvq4lNw22yG8EMsdItIH9/04CffrNWPifW65WGAvlrlt/RaObJl6vgMcC9wnTjopcDbw\na1wxlmbg6iz1VVZE58svpC2/ULb54cNHkYt8Np4Hz+tAd6CriNQA19BaiEXJUiGWYlqDMUqfbHn1\n/AT4SZxTd3qb7yiGn8Px3DPbqo7VnvaYbL+5EfABWu3w8Ums2ecmrYHmsRBLJp9bqhTD3LZ+C4tF\n7vqEZE062aqO1VbUaw795oG8mW58RblUNTOKA8vV4xPmLZrHVXddxcM3PBwy6WQjX36q2ntNTT1A\nQsGfyuJrouP5TEVsuXqMUsVy9RQR8TT7bJh0/Ogbn2/TjR+xXD1Gtgl69WRC2Wr8hbLNzVs0jytu\nvYLHfvJYSIDHy5659LWlcd0zP3tvP70P+GJMu8m5SAYI2tnb0sYhNY0/GbfKQr3f5ajxm42/9PsF\n0/h9SVuafXhefCCut8fRvb6CfHR6RJsCbFm7jrc21cf0V1gNvnRt85liGr+RbUzj9zHRNvvgsWjN\n/oEHFrC451xaRuwN3dthVWeq/ngK2zcvjmk3W3b2tjT+4AJvNKmmO/YD5ajxG+WBafwFJFqznzLl\nTlavbub1zQ/ReEkjV948lXtnvcmmTavY2HEZTZe0avZX3jyVfZ/2oKXiJHil9fNrQWlu+SSn427L\n/l5swt0wjNQoW8Gfqk+7qrJ20x8Z0v9MRIRNm1bRv/8INm9/h9WdnuaZpz6kb88jna390y/DhVtB\noPHorby48BgqK5fQ9CV3jLXAEHeu8vfD4B+xmn1Fz8nsycJzhgv48LQJ+TbPJPV+t7TARx/B559H\nbnv3whlnxF6/dy/87GfummuvhR490hpbqRViMRt/afebDVNPzgW/iFyCC+LaB8xIlMwqH4QL8Tfe\nmcOxR16BiIS8TOIJ+NCiaed5cNTd/P2V62DvRHr2nMzq1XUw8CS4eg/vPLQOVjxBjx6Tod8sGOk0\ne0Y2wcsz2du0A14dB68K7PgYegwElH2dsqPZJ2N/v+eee0IJpQBXt6ShwQnO3bsjBe2ZZ8Z2sm8f\n3HUX7NkTeU9LC/zyl7HX79kDJ58Mn3/Oik2bqK2sdPcAfBLnuffuhdNPhy5dIrfu3eMLfhH49FN3\nTUtL7Pl2EJEqXKDWGcATeKkZkpmzIjIc+DYwFBfduypeH5kWxU6HFStWFEzwF6rvcuo3qEhkUnM3\np4I/2aIWNTV1EVp0Iu060+MRQrz3Bl585RjYO5FgEewlS+rjCnhQJ8wvaITNM+FjtyhL5/lwsudy\nefJKWLiAffJR6zEInev8+xPY+1FQs6+Hra7Pim6Xp6TZV+zdwOgBX4Pq6ojj1dXHMfuBG2H8+Eht\nedXnsGAWbNnCtm3bIhvbvz9W0HbtChUV8QV/UNAecIC7tkeP1nvi0bkzPPAAdOnCttmz4YYbWvuJ\nR5cu7h9RsnTqBD/9afLXx5J2IRZVXQ18V0QuBcYAcQV/IYj5nMug73LrN1NyrfEnLGoRflFQADst\nuj6Bdp2F490uJyTEj9gDH4QJcSCugG9qiivgVTW+Zr99c6tmH9ZuQs2+OX4amIqKXYw+tg4+/BA6\ndHCbCNX9D2b2pFNhyhQniMNRDQnamC0enTqlJmg7dkxN0IrA8ce71336QBbSyWaTTAuxiMgsYByu\nVKNhFA25FvwJi1pE0M8Tss3NJNSu4x3fvj2165ubW4X4akJCPEQ8Ad+hA/SNI+Abu8bX7J8fx96P\nlsQ8YqTNvqH1+MEdGD28Pub6tGzw4YI2Dg2pCPksU8i+UySpQize/g0iUg3cAlyfvyG2TTl+zuXW\nb6bk1J1TRG4Cuqlqnbc/A1ivqr8Iu8b83YyckmI+/nbnrHf8XJz23xu4S1VjSora3DZyjV/dOTcS\nmZJxIC7dbYhC+VgbRgLanbMAqvo7XM2JhNjcNvxKhxy3/wJwtoj0EZH+uKIWL+S4T8NIh/BCLDZn\njZImpxq/qn4iIlkvamEY2SCfhVgMw08UPGWDYRiGkV9yberxLSLSVUQSVV8yjKLF5rbRHgUV/CJy\niYh8KCJrROTKPPVZJSILgU+AG/PRp9dvFxF5UERWi8haEbm2/buy1reIyAte3++KyFn56tvrv7OI\nvC0is/PYZ4uIrPfm1nsiEutjm1w7k0TktRTvyfu89vq1uV0Gc9vrtyGTuV2wXD3JRkjmgJhozTzR\nDXheVb8pIr2Bt0Vkrqquz3XHqqoi8nVvzeVLwB3AH3Ldbxg/AP6ex/7AzakWVa1u98rk2kqKAs5r\nsLldLnMbMpzbhdT4QxGSqvoJEIyQzCmquktVFwP7c91XVL+fqepC7/WnuMnSK4/9B0OHBwEr8tWv\niIwExgOP56vPYNe0eurkk4LMa7C5TfnMbchwbhdS8CcX1VuCiMjRQGdVfTuPfd4oIluAa4Hp+eoX\np4F+l8II4d3eT+FXROR/PDPEZyLylIgMDF4kImNF5M8i0igiz4nIAhGJm5tCRIZ612z1zDk/EonI\nnXEFcIGIbBGR64DLgNG5fUz/YHM7bzR5c/tlETk71ZsLKfgPwP00DdJCnjWVQiAiBwOPApPy2a+q\nzlTVPjhXxbz4pYvIt3B5bd7PR39xuEBVh+FyZEwELgCOALYA870xVgLPAfNwiscDuIjcGESkAqfB\nv4zTLi8ErgT+zTt/MS74ay5wODAKz+SUg2fzHTa384eqjvLm9k3Ab0QkpZzkhRT8G3FRkUEGUhhb\nWd4QkYOARcCNqvpGIcbg/STv7o0l11wOXCoir+M0sQtF5Ht56Dea84H3cO7LW4GpwGhxeXbOBbaq\n6ixV3amqzwDPt9HOLlX9iaru8D7DnwJf985P9u7toKo7cAusAmzK1YP5BZvbhZnbqroUp9gMTuW+\nQhZieQG4Q0T6eOM4CS8feh7J2080EemJ+2LUqeof89Wv1/cQoMlbADsJaFbVz3Ldr6qeEjaGYD6c\nu3Ldbxh9RKQvUAH0xAl/VHWXiHyG0/AHA2ui7kv03gwCojW8BlpNlIOBmcCPw+Y1wLK0nyB9bG7n\nkELObe9Xag9V3SQiY4D+eHM7WQom+AsV1SsJojVVNS13vxT4DnAscJ9nE1bgbFVtyHG/4BbanheR\nDjhXv0vz0KcfeBRXTAVgWnB+eXPgINwa0zDcelM4Q4DNcdpbjzMVRV8bXKvaCvSgNfK3I+5z/jyj\np0gSm9tlM7crgSXeM28HLktZdqqqbbaV3Iazqx/pvf5PYCnO7n4QMBv4nXduINCEs9N3B64CdgE/\n9c5PAv7ive6BM1H+EKjCCbv3gYu98zfifgEcDRyMq+q1PzgO22zzy5aWjV8sMtDwP+G+99cBy3HC\n/x2cY8FlAKr6MfBV4HvABlxhlUU44R/ZoLPbnw18EfgYJ9j/Q1XnepfcAzyLy9n/Km7BmHhtGUYh\nSSlXj0TVKFXVNmuUSpJ1SQ3DT4jIcuBuVX0sw3aOBf4CVKhqWXj2GMVBqoK/Gy4icQhworrCFd1x\nWlQoUhE4SsMiFcXVJe2gqr/N5uANI1NEpCPOnPM0bv5+C+ebPVRVG1Ns6wTcr4m/4RaCZwPvqOq/\nZXXQhpEhKZl6NH5kYJuRiuLqkn7LO24YfuQSnK3+PaAGODNVoe/RBXgQFyfwHPBXfFSS0TCCZMOr\np80IXPVpXVLDAFDV/cA5WWrrJVzQlmH4mmwI/oQRuBJVlzTezWJ1SQ3DMNJC0yzvmY3I3YQRuKr6\nO1X9f6p6qcYpRh2krq6OxYsXF9zFKZOtrq6uZPrNtM107k/lnmSvTea6tq6ZNGlSQT7TXGyFmJ+l\nMjdTvS9b8zPR+cWLF1NXV5eR0M5E8FuN0jBqa2tLpt9M20zn/lTuSfbaZK4r1OeWbwrxnKUyN1O9\nL1vzM5efWapePRGRgbjoxmtwHgy34bwivqeqi1JoU+vq6qitrS2bL6FRHNTX11NfX1/oYRhGBIFA\ngEAgwLRp09A0TT0p2fhVdScuxD0ec9IZgGH4FVNEjFKlbGvuGoZhlCspmXpyMgARLfQYDCMegUDA\ntH7Dt4hI2qYeX2j89fX1BAKBQg/DMCIwoW/4kUAgkPHak2n8hmEYRYhp/IaRA2xOGn7ENH7DyCFm\n4zf8TCYavwl+wzCMIiTvpp5sF2IxU49hGEZy5N3Uk0YhluNwuc6/ADyuqvPjtGkav+FLzNRj+Jl8\navwtwL24UnbBzrsDs4CTgVOBO0Skt3d6uap+F/gGcF46AzQMw0gFVeWWabeEkpoFXxut5LQQS5gq\nfwPw8yyM1zDyhmn7xUO4gJ//zHzu/9P9LHh2QcRro5VsuHMmLMQiIh1EZAbwjKquyEJfhmEYQHxh\nP/+Z+cx6bBaNpzfy00d/yqw57vXMOTNN6w8jp4VYgNuBE4HeIjIyaPuPZvLkyQwePBiAXr16MXr0\n6JC2FVz0tX3bz/d+uMOBH8Zj+5H785+Zz70L7qWiUwX/u+J/aTy9kak/msqnX/gUBFY0rkBRaICV\n3Vey4NkF9K7q7Zvxp7ofCAR45JFHAELyMl3ScucUkUnAKeqKrX8dqFXVq71zjwHzVPXpJNuytMyG\nLwnY4q6vUFW+P/37zLhtBgAnXXISr456laF/GsqGoRtoOqwJWSToBZ5Mex5XVFMAhfFvj+eVJ19B\nJK31UN8QyEJaZivEYhgJMKFfWKIXZqNt9yurVgLwwc4PaDqsCd4HPVKdZHofl0A+KKWkVes3UjT1\nRBdiEZEaXCGWHwJ/xhViuV5Vm7M9UMMwSp9wrT4o6I8fezwTzpsQYbsXhKajooT9P4A9IO8LBzYd\nyP6K/eh7SlWXKoYOGYqqsvS1pUw8f2KhH7PgWCEWw0iAmXpyS7iQD5pfgsJ+3JhxIUE/c85MWlpa\nnIbv2e6lv8QI+5F9RtL3kL6oKmMHjeXu6XcX9Pn8TDYWdw3DMNolWtCHa/QTz5+IqoaE/fdnfZ8N\nQzeAwJvd3uSH9/6QplObANjTsoeqd6oYz3jkEAm1bcI+eSxXj2EYeWHeonlcdddVPHzDw0w4b0Jo\ncTa46Dr/mflMempS5CKtAO9BB+1AS3Wr82BlQyVzJswpa7NNJpG7vtD46+vrzavHMEqIaO0+XJuP\nNt2s7L4y5H/fNCrKbg/wD9AdypHbj6Rvn76h9svVXh/06skE0/gNIwFm40+OeLb6cO1+4vkTmbdo\nntPmBzVRsbaCgX8fyHunvhdytQy5ZA5qgmU4u/1uz27fJ3W7/ZQpd7Jmze6Y49XVXZk9+5YsPn3h\nMI3fMIyC0ZatfuacmVx47oWt2jzQvK+ZD/p/EOFq2bCngep/VNO3pS8c4g4nI+zDBfzq1W/T3NwN\ngKam3ezd+z9x7qjP0lMXDtP4DcPIK/FMOAlt9YOaqGyo5FsDv8UD6x9w2jzAMpAdrdp8sN1kNfpw\nYb9iRQPbtz/inamnVbCHv26lpqaeQCD2eDFS9Bq/YRjFQbR2HwqkimerB5oGNfHrRb9m3NHjkLWe\njDoEdEBiQR9tpglq8hUVHRg+/LA4wt5IlbQEv4h0BQ5V1ffaua4TcBrQSVUTRvOaqcfwI+Vs449n\nt2/PhNM0qCnCDRMAgcZjG/nuhO+2uRCbWIuHoPa+fTts2hTcL1+yYepJNXI3ohAL0GYhFuBo4Dhc\nts42Bb9hGP4hWrMPHgvX7m+quym0D8Ta6j2iPXDiLbyaFp88QSV52rRpabeRqsYfLMTyDC7rZngh\nlhNwKRtWiMgiVf1UVV8Xkc+AqWmP0DAKRDlo+8lo9hPOmwDQvgkH0OGxJpwpU+7k9Rd3U1tbD8TT\n6CH7wr5rqM2ePRsYPXow4Lx6jNRTNuwCFovIYWGHQ4VYAEQkWIjlyayN0jCMnJCMZr/g2QWoaox2\nH8+EEy3kIZHpJlu0CvjOnf9MZeVkgNB6AEB19YiSceHMFtlY3E1YiCWM4s6DapQlpWLjj6fVB48n\no9nPnDOTE0ecyLj9kdr96tXrmHrTTO67a2XoWD61+XBNHqC6utYEfJLktBCLiBwD3AQcJSLXquo9\n8RqwQiy2b/u521+ybElIqw8vRDL/mfms2LkiolDJW2++5Y4F5XuDS4rW/W9HIE2ns21bAwC9eg2m\n+d0Gtm+fzPpVALXeDZOBQNh+wDUSIt4+UfsbCP6z6NbtzxxwQDMtLQ1UVHSgX7+WUP/V1SP42tdO\nzPn755f9gBViMQwjSCKNPngu2s8+2v8+vFDJzo878nHz+pg+9m7qRtMnb0cdrSdWm0/mWLxr7qRn\nz1URGjyUVqRttghkoRBLJhp/eCGWO0Skj9feSXjePoZh5J54dvrwc9H2+onnT+Sscy/ntZ7LI2z2\nr3VaTtUHp7B9c0NMHz17Ts7iiBOZaswWny+sEIthJCBQBDb+eHb6aO+caHv9hPMmsGrtB7Q0nwSv\ntCqMLSjNLZ/kYJRd6dlzchxt3gR9obBCLIbhc9oy5STS6IGEWv1Z517O0H7nsH5JfUxfFT0nsyej\n0ZqQLwYsZYNhJMAv2n4iU84118zgiWW/pOmSVo3+ypun8vyiNfzqV99PqNWvqviAof0S6W+p4FMh\nf++98MorsGGD2777XfjOdwo3Hh9iSdoMw8ckWpwFGDXmEt6p/h0c2dR6wzuVHLnmXN5+/Ulqa+tZ\nEkerr6lxx+Kd69lzchx3TOjf/2KGDx8Vczwvi6+LF8Mbb7QK8uB2//1wxhmx1y9cCE1NcMghbjv0\nUKiszO0YC0DRJ2mzXD2GH8m1jb8tEw64YKhlry1n1YjlITPNUWMv5ZTjxzJ79i1s370OXh0Hr4bf\nq2yvWJf2mCoqdjF6dH3M8erq47In4DduhA8/dH/DBfk118Cpp8Ze/+absHatE+JHHQVf+IJ7ncil\n8cILszNOnxL06skE3wh+wyg32vLGAVi9upl3tqyD4XsBaBm+l3eWrqPP6pEACe30Q2tij0XjUhfE\nXpe2gN+zx2VQCxfmJ58MY8bEXnvvvRAIOOE9YIAT5CNGwGGHxV4LMNUyvoQTVJLzmasnJ5jGb/iR\nXM3HKVPuZPXqZl7f/BCNlzRy5c1TuXfWmwwfXhEhdLfseBdOjkyTwMkr2bImgYBMgaSF+7598Mkn\nTpAffDAMGhR7zS23wM9+Bv36OUEeNLHEE/oAM2akP3DDNH7D8BvtmW8A1qzZzYuvHA0XbnU5b47e\nyosLj0FkZcR1mZpyEmv1XWH/fqelV1TE3vjII04r37ABPv0U+vZ1gvz66+ML/ro6uP126NgxqXEZ\nmVEyGr9h+JFUbPzBVMObt7/D6k5P88xTH9K355FxFz9VFfrNgpHeouzIJnh5JqpfiriuPVNOm4Kd\nMK3+xRfh8cdbzTC/2wBdb4Uf/ADiCY+aGmdLHzDAafGd2hET8f55GL4mp4VYksVMPUaxs2bNbpYs\nqYOBJ8HVe3jnoXWw4gkgVrBmbMJpboaHH2b2oP3QeXOrTf1LX4Lp02Ovr6yEY46Bc85pNcP06wed\nO8dvf8gQtxm+JBumnpTcOaMLsahqm4VYRGQ4UIdL5Ha7qr4ep01z5zSKntraepa8fBRcOMm5V75T\nCQvnUHPySqJrvA4ceSLrm7sQmbRW+YJs5+Np14cE+ZS/bWVN5yNi+qru/hmz++xoXRwN/j38cOjf\nP6fPafiHfLpzplSIBbgO+I53/C7gynQGaRj5ImiyUVXWbvojQ/qfiYi066+e0Hyz61T405+cMK+q\ngq98JbEJp+e/wB/+4AT5EUcw+6IxcNppOXpSo5zJdSGWvt4/gOCvBcPwNc5kUw+d58Ggmfz9letg\n70QibOk7dzpB/vnncPTRQBvmm2c/hx//1QnzU04B2rLNnwiW1sDIA7kuxLJDRA70Xm/OQl+GkTv2\n7vVeeNr7Kc2weyZ8PAFWrHC+5hs2OBfHQw6B2lr4r/8C2vDAOexzF3kahuWsMQpNTgux4MxCs4Fm\n4MeJGrBCLLafrf3zzpvCxx/voVevwQChwiEnnODyxwQCAdi+nVovl0vg7bdhyxZqd+yAQw9lW4ex\n0HG6096HAENXwMbpzo3xf2YQ+OAD6NaN2tNPj+j/y6f+C2vW7I4oVALQvfuGCO+gQr8/tl+8+wEr\nxGIYYezeDc89Bxs3Uvsfr7Lk77GJYmtq6gktsm7fDr/8ZauHS3A78EBqaut58cPfw9WtBUp4aDyn\nHf4llixJ32/aMLJFwAqxGCWJamxCrg0bYNs2uO++2Ov37YM5c5zwDgURKXT9PuyeQUzJ5549nQ97\nHCJs9WtxWn+WomUNwy9YIRYjf+zfD5vD/M43boRvfAOiI1z37YMTTogM/x8wwPmiq8Ze3707PPWU\ne11b70q6dp4PI++Ht473FmeTo0PFBnqu7gurYd/O3XRa4YKhOlRuSPuxDcNvWCEWI3NaWmDLFifM\njz46fuj+sGHw0Udw4IGR5pVJk+CAAyKv7dwZ1sfWfU0eb3H2gkbY7C3OJsnKl5dm0K9hFAeWssFI\nTHD9J17OmUmTYNUqJ+w/+QR69HCCPBCAgw6Kvf7FF6FPn4ho0SlT7mTN2XfEXJpxjvfO81vNNSev\nhIUL0m/LMEoQXwh+S9LmAx54AN59N9KmvmkTvP02HBEbPcpll7mApEMOcdGiXbq03f6AATGHQj7z\nMcQ7lhzDhnVh+T+upTEskKpq5VSGDft2ym2Fe+MYhl8IOsIUfZI2y9WTA159Fd57L3aB9Fe/gpEj\nY6/ft8+F/J9ySmuhiwEDEifgOvvs3I4/Tb50/jAe3781IpBq//itnHNBdUHHZRjZIujVkwlWerFY\nCEaLhi+MbtgA3/wmVMcRatddB//4R2Q+l0MOgbFj3WKoD2gtDRjpgRPhepki1912Hcs/Wh6REllV\nGTtoLHdPvzsbwzYMX2ClF4uZpqbIqkUnnhg/5/nkyS56NHxhdMAA6No1frt3F5GQS9MDJx4m3I1S\nxzR+P/P5506g9+zpPFmiue46V/CiuTlSI7/pJjj++LwPtxA4jT+YyvhVeGg8fPwKNTXT0tb4s4nZ\n+A0/U/Qaf0nwX/8Fc+e2au47d7pFz7vvhglx3AlvvhluvdX9U0hQqSmfBLNSRpOxh00bVFd3ZfP2\nS1k1YjktAh3+aTkjVl1KdfXYnPRnGIYjacGfTvEVEekEnAZ0UtUXEl1XEqae0aNbF0UPOQR694YO\nHRJf77O86bnwsGmPBx+8mZMuOYmWsGLiVfvW8eCDT+Ssz1Qo6vlolCzZMPW0IZkcIlIlIguBT4Ab\nw45fIiIfisgaEUmUZ/9o4DjgnLb6CAr+ombcOPjnf4Zjj3U1StsS+gYA85+Zz8qqyFTGK7uvZMGz\n5ndvGImora3N2AU+GY0/1eIrIVT1dRH5DJia0SiNkmTZX5cxbv84ZG2kB87S15Yy8fzMFnmzgdn4\njVKlXcGfavEVEakFzgUWq+pz2R+yUSqYB45hFIZ0F3cTFl9R1QAQiLq+8KuXhpEipu0bpUq6gr+t\n4ishROQY4CbgKBG5VlXvideYFWIp/H6wHODWrWvZ+NlyRh4+ARGxQiK2b/s+2Q8UohBLNouvRLVr\nhVh8xLxF87jqrqt4+IaHfWFnLyTh//AMwy8EslCIJVXXk/DiK2eLSB8R6Y8rvpLQXdMoDlSVWY/N\notc18v8AAAUISURBVPH0RmbOmUlJBtYZhpGUO2d3EXkPuBO4SETWACNoLb7yElZ8pSQId680t0qz\n8RulSzJePVZ8JQGFiHbNFUFtv2mUS2fcNKiJmXNmMuG8CREJzwzDKH4sZUMGFCLaNVe0FUxVrrZ+\ns/EbpYovBL8VYik8fg+mMgzDEXSEsUIsRsZYMFUsNh8NPxL06skES8ucAa2FRCLJpJCIYRhGMmSS\nltkXmcTq6+sz/g9mGNnG5qThRwKBQMbmcdP4M6CUvHqMWGxx1/AzmWj8JvgNwzCKkLyYekSkq4gk\n8ufPCDP1GIZhJEdeTD0iUoUL1DoDeEJVp3jHL8FF8+4DZqjqw3HuPQ6YBHwBeFxV58e5xjR+w5eY\nqcfwM7muuZt2IRZguar+TUQOBH4GxAh+wzAMI7+0a+pR1V2qupjItMuhQiyq+gkQLMSCiNSKyEwR\n+XKYKn8D8PMsj90wcopp+0apkq47Z5uFWFT1RlV9TkQ6iMgM4BlVXZHhWH2LqnLLtFssm6VhGEVB\nTguxALfjzEO9RWRkvHUAKP5CLEuWLeH+P93P8WOPp3dV74KPx/azV/giiB/GY/vlvR+wQiz+QVU5\n6ZKTeHXUq4x/ezyvPPmKZbMsEQK2uGv4kIAVYik8lsO+dDGhb5QqVoglA0I57A+LzGFvtn7DMPxM\nMl49O1V1mKoOUNUDVbVaVZeo6hxVHeqdW5SPwfqNtnLYG8VPuI3fMEoJX6RlLlYsh71hGMWI5eox\nDMMoQiwts2EYRpkQsLTMhpE7zJ3T8DOm8RuGYZQJpvEbhmGUKUWv8RuGYRj5wwqxGEYCbE4afiQv\npp4MC7EMB74NDMVF966Kc42Zegxfcs8993DttdcWehiGERffFmJR1dXAd0XkUmAMECP4DcOvbNu2\nrdBDMIyckNNCLN7+LOBb3jUlS6HMArnoN9M207k/lXuSvTaZ68rFnFOI5yyVuZnqfdman7n8zHJa\niMXbvwGYAtySyUD9jgn+zO73o+BvaGhIqp9iwAR/ZveXmuBPNx//TUA3Va3zzs0A1qvqL6LuORc4\nF+gN3KWqf4nTrhn4DcMw0iCXNv54bARqw/YH4lI0R6CqvwN+11ZD6Q7cMAzDSA8rxGIYhlFmtKvx\nex48rwPdga4iUgNcQ2shFqVMC7EYhmEUIwVP2WAYhmHkl7ykbEgn6ldEOonIGSJydq7GZRhBchmZ\nbhiZkOzcTEVm5lTwi0iViCwEPgFuDDt+iYh8KCJrROTKBLcfDRwHnJPLMRrlTapzVESGi8jjIjJP\nRMYUYsxGeZCG/ExaZubU1CMi3XDRvUOAEz1X0O7AO4RF/QJHRUf9evcPAqaq6vU5G6RR1qQ6R0Xk\nP3HrW4pzUU6kuBhGRqQjP5OVmTnV+DON+jWMXJPqHAX6quqnqvoZUJXn4RplRBpzM2kKUWy9zahf\nIBB1vfn5G/km4RwFdojIgd7rzXkdlWG0PTeDtCszC5GP/wBc4rcgLUT+RwNARI4BbgdOFxFLkWjk\nk7bm6L3AbODnwM/yPC7DSDg3U5GZhdD4k436fRO4PE9jMoxwEs5RVX0duLgAYzIMaHtuJi0z86nx\nW9Sv4Xdsjhp+JatzM6cav0X9Gn7H5qjhV3I5Ny1y1zAMo8ywYuuGYRhlhgl+wzCMMsMEv2EYRplh\ngt8wDKPMMMFvGIZRZpjgNwzDKDNM8BuGYZQZJvgNwzDKDBP8hmEYZcb/B8FnIQ7KwETnAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fc062d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# arange类似python里的range\n",
    "t = np.arange(0, 5, 0.2)\n",
    "\n",
    "fig = plt.figure()#figsize=(10,6)\n",
    "\n",
    "#行, 列, 序号\n",
    "ax1 = fig.add_subplot(221) \n",
    "ax2 = fig.add_subplot(222)\n",
    "ax3 = fig.add_subplot(212)\n",
    "\n",
    "ax1.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n",
    "ax1.grid(True)\n",
    "ax1.set_title('plot')\n",
    "\n",
    "ax2.semilogy(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n",
    "ax2.grid(True)\n",
    "ax2.set_title('ylog')\n",
    "\n",
    "ax3.loglog(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n",
    "ax3.grid(True)\n",
    "ax3.set_title('loglog')\n",
    "\n",
    "fig.suptitle('normal vs ylog vs loglog')\n",
    "#fig.subplots_adjust(hspace=0.4)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
